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Technical Brief

A Re-Engineered Software Interface and Workflow for the Open-Source SimVascular Cardiovascular Modeling Package

[+] Author and Article Information
Hongzhi Lan

Department of Pediatrics,
Stanford University,
Stanford, CA 94305

Adam Updegrove, Shawn C. Shadden

Department of Mechanical Engineering,
University of California, Berkeley,
Berkeley, CA 94720

Nathan M. Wilson

Open Source Medical Software Corporation,
Santa Monica, CA 90403

Gabriel D. Maher

ICME,
Stanford University,
Stanford, CA 94305

Alison L. Marsden

Department of Pediatrics,
Stanford University,
Clark Center E100B 318 Campus Drive,
Stanford, CA 94305-5428;
ICME,
Stanford University,
Stanford, CA 94305;
Department of Bioengineering,
Stanford University,
Stanford, CA 94305
e-mail: amarsden@stanford.edu

1Corresponding author.

Manuscript received December 5, 2017; final manuscript received December 11, 2017; published online January 25, 2018. Editor: Victor H. Barocas.

J Biomech Eng 140(2), 024501 (Jan 25, 2018) (11 pages) Paper No: BIO-17-1574; doi: 10.1115/1.4038751 History: Received December 05, 2017; Revised December 11, 2017

Patient-specific simulation plays an important role in cardiovascular disease research, diagnosis, surgical planning and medical device design, as well as education in cardiovascular biomechanics. simvascular is an open-source software package encompassing an entire cardiovascular modeling and simulation pipeline from image segmentation, three-dimensional (3D) solid modeling, and mesh generation, to patient-specific simulation and analysis. SimVascular is widely used for cardiovascular basic science and clinical research as well as education, following increased adoption by users and development of a GATEWAY web portal to facilitate educational access. Initial efforts of the project focused on replacing commercial packages with open-source alternatives and adding increased functionality for multiscale modeling, fluid–structure interaction (FSI), and solid modeling operations. In this paper, we introduce a major SimVascular (SV) release that includes a new graphical user interface (GUI) designed to improve user experience. Additional improvements include enhanced data/project management, interactive tools to facilitate user interaction, new boundary condition (BC) functionality, plug-in mechanism to increase modularity, a new 3D segmentation tool, and new computer-aided design (CAD)-based solid modeling capabilities. Here, we focus on major changes to the software platform and outline features added in this new release. We also briefly describe our recent experiences using SimVascular in the classroom for bioengineering education.

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Figures

Grahic Jump Location
Fig. 1

The multilayered multiple-component architecture of SV comprised of main application, solvers, and optional licensed modules. The main application consists of three layers: interaction layer, core modules, and external packages, supported on three major operating systems.

Grahic Jump Location
Fig. 2

Data types and their inheritance relationships in SV. The classes in white are used in open source modules, while the classes in gray are for licensed modules.

Grahic Jump Location
Fig. 3

The redesigned SV GUI, containing a data manager, a multiview display window, and multiple plugins for data processing. In this example, a plugin for path planning is activated, providing options for a user to create and modify a path.

Grahic Jump Location
Fig. 4

The SV pipeline encompasses the complete process for cardiovascular modeling and simulation, from image visualization, to anatomic model construction (including path planning and image segmentation) to meshing, BC assignment, blood flow simulations, and analysis

Grahic Jump Location
Fig. 8

Comparison of lofted surfaces between the various lofting methods: (a) PolyData model using a Kochanek–Bartels spline lofting, (b) PolyData model using the custom b-spline based lofting method, (c) OpenCASCADE model using the default lofting method in OpenCASCADE, and (d) OpenCASCADE model using the custom b-spline-based lofting method [44,71]

Grahic Jump Location
Fig. 7

A PolyData model created by SV using 2D contour groups. Faces are automatically extracted with specific types (wall or cap). In the interface, different colors can be assigned to faces for easy recognition.

Grahic Jump Location
Fig. 6

3D segmentation of an MRI scan of the aorta and iliac arteries using the colliding fronts algorithm by (a) placement of colliding fronts seed points and (b) final smoothed model of the aorta and iliac arteries

Grahic Jump Location
Fig. 5

SV provides several methods to create and modify contours, loft solid models of vessels, and interactively preview the model during construction as new segmentations are added

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